SoroushVahidi/scidocs huggingface dataset:
Memristor-The Missing Circuit Element LEON 0
(1971)

A new two-terminal circuit element-called the memrirtorcharacterized by a relationship between the charge q(t) s St% i(7J d7 and the flux-linkage (p(t) = J-‘-m vfrj d T is introduced os the fourth boric circuit element. An electromagnetic field interpretation of this relationship in terms of a quasi-static expansion of Maxwell’s equations is presented. Many circuit~theoretic properties of memdstorr are derived. It is shown that this element exhibiis some peculiar behavior different from that exhibited by resistors, inductors, or capacitors. These properties lead to a number of unique applications which cannot be realized with RLC networks alone. I + ” -3 nl Although a physical memristor device without internal power supply has not yet been discovered, operational laboratory models have been built with the help of active circuits. Experimental results ore presented to demonstrate the properties and potential applications of memristors. (a) I. 1NTR00~cnoN I + Y -3 T HIS PAPER presents the logical and scientific basis for the existence of a new two-terminal circuit element called the memristor (a contraction for memory (b) resistor) which has every right to be as basic as the three classical circuit elements already in existence, namely, the resistor, inductor, and capacitor. Although the existence of a memristor in the form of a physical device without internal power supply has not yet been discovered, its laboratory realization in the form of active circuits will be presented in Section II.’ Many interesting circuit-theoretic properties possessed by the memristor, the most important of which is perhaps the passivity property which provides the circuit-theoretic basis for its physical realizability, will be derived in Section III. An electromagnetic field interpretation of the memristor characterization will be presented in Section IV with the help of a quasi-static expansion of Maxwell’s equations. Finally, some novel applications of memristors will be presented in Section V. 1 + ” -3
Millimeter-wave antennas for radio access and backhaul in 5G heterogeneous mobile networks
(2015)

Millimeter-wave communications are expected to play a key role in future 5G mobile networks to overcome the dramatic traffic growth expected over the next decade. Such systems will severely challenge antenna technologies used at mobile terminal, access point or backhaul/fronthaul levels. This paper provides an overview of the authors' recent achievements in the design of integrated antennas, antenna arrays and high-directivity quasi-optical antennas for high data-rate 60-GHz communications.
Frequency compensation of high-speed, low-voltage CMOS multistage amplifiers
(2013)

This paper presents the frequency compensation of high-speed, low-voltage multistage amplifiers. Two frequency compensation techniques, the Nested Miller Compensation with Nulling Resistors (NMCNR) and Reversed Nested Indirect Compensation (RNIC), are discussed and employed on two multistage amplifier architectures. A four-stage pseudo-differential amplifier with CMFF and CMFB is designed in a 1.2 V, 65-nm CMOS process. With NMCNR, it achieves a phase margin (PM) of 59° with a DC gain of 75 dB and unity-gain frequency (fug) of 712 MHz. With RNIC, the same four-stage amplifier achieves a phase margin of 84°, DC gain of 76 dB and fug of 2 GHz. Further, a three-stage single-ended amplifier is designed in a 1.1-V, 40-nm CMOS process. The three-stage OTA with RNIC achieves PM of 81°, DC gain of 80 dB and fug of 770 MHz. The same OTA achieves PM of 59° with NMCNR, while maintaining a DC gain of 75 dB and fug of 262 MHz. Pole-splitting, to achieve increased stability, is illustrated for both compensation schemes. Simulations illustrate that the RNIC scheme achieves much higher PM and fug for lower values of compensation capacitance compared to NMCNR, despite the growing number of low voltage amplifier stages.
Time-Frequency Masking in the Complex Domain for Speech Dereverberation and Denoising
(2017)

In real-world situations, speech is masked by both background noise and reverberation, which negatively affect perceptual quality and intelligibility. In this paper, we address monaural speech separation in reverberant and noisy environments. We perform dereverberation and denoising using supervised learning with a deep neural network. Specifically, we enhance the magnitude and phase by performing separation with an estimate of the complex ideal ratio mask. We define the complex ideal ratio mask so that direct speech results after the mask is applied to reverberant and noisy speech. Our approach is evaluated using simulated and real room impulse responses, and with background noises. The proposed approach improves objective speech quality and intelligibility significantly. Evaluations and comparisons show that it outperforms related methods in many reverberant and noisy environments.
Depth Images-based Human Detection , Tracking and Activity Recognition Using Spatiotemporal Features and Modified HMM
(2016)

Human activity recognition using depth information is an emerging and challenging technology in computer vision due to its considerable attention by many practical applications such as smart home/office system, personal health care and 3D video games. This paper presents a novel framework of 3D human body detection, tracking and recognition from depth video sequences using spatiotemporal features and modified HMM. To detect human silhouette, raw depth data is examined to extract human silhouette by considering spatial continuity and constraints of human motion information. While, frame differentiation is used to track human movements. Features extraction mechanism consists of spatial depth shape features and temporal joints features are used to improve classification performance. Both of these features are fused together to recognize different activities using the modified hidden Markov model (M-HMM). The proposed approach is evaluated on two challenging depth video datasets. Moreover, our system has significant abilities to handle subject's body parts rotation and body parts missing which provide major contributions in human activity recognition.
Cloud Task Scheduling Based on Load Balancing Ant Colony Optimization
(2011)

The cloud computing is the development of distributed computing, parallel computing and grid computing, or defined as the commercial implementation of these computer science concepts. One of the fundamental issues in this environment is related to task scheduling. Cloud task scheduling is an NP-hard optimization problem, and many meta-heuristic algorithms have been proposed to solve it. A good task scheduler should adapt its scheduling strategy to the changing environment and the types of tasks. This paper proposes a cloud task scheduling policy based on Load Balancing Ant Colony Optimization (LBACO) algorithm. The main contribution of our work is to balance the entire system load while trying to minimizing the make span of a given tasks set. The new scheduling strategy was simulated using the CloudSim toolkit package. Experiments results showed the proposed LBACO algorithm outperformed FCFS (First Come First Serve) and the basic ACO (Ant Colony Optimization).
A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments
(2010)

Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. However, users are charged on a pay-per-use basis. User applications may incur large data retrieval and execution costs when they are scheduled taking into account only the ‘execution time’. In addition to optimizing execution time, the cost arising from data transfers between resources as well as execution costs must also be taken into account. In this paper, we present a particle swarm optimization (PSO) based heuristic to schedule applications to cloud resources that takes into account both computation cost and data transmission cost. We experiment with a workflow application by varying its computation and communication costs. We compare the cost savings when using PSO and existing ‘Best Resource Selection’ (BRS) algorithm. Our results show that PSO can achieve: a) as much as 3 times cost savings as compared to BRS, and b) good distribution of workload onto resources.
QRSF: QoS-aware resource scheduling framework in cloud computing
(2014)

Cloud computing harmonizes and delivers the ability of resource sharing over different geographical sites. Cloud resource scheduling is a tedious task due to the problem of finding the best match of resource-workload pair. The efficient management of dynamic nature of resource can be done with the help of cloud workloads. Till cloud workload is deliberated as a central capability, the resources cannot be utilized in an effective way. In literature, very few efficient resource scheduling policies for energy, cost and time constraint cloud workloads are reported. This paper presents an efficient cloud workload management framework in which cloud workloads have been identified, analyzed and clustered through K-means on the basis of weights assigned and their QoS requirements. Further scheduling has been done based on different scheduling policies and their corresponding algorithms. The performance of the proposed algorithms has been evaluated with existing scheduling policies through CloudSim toolkit. The experimental results show that the proposed framework gives better results in terms of energy consumption, execution cost and time of different cloud workloads as compared to existing algorithms.
Systematic literature reviews in software engineering - A systematic literature review
(2009)

Background: In 2004 the concept of evidence-based software engineering (EBSE) was introduced at the ICSE04 conference. Aims: This study assesses the impact of systematic literature reviews (SLRs) which are the recommended EBSE method for aggregating evidence. Method: We used the standard systematic literature review method employing a manual search of 10 journals and 4 conference proceedings. Results: Of 20 relevant studies, eight addressed research trends rather than technique evaluation. Seven SLRs addressed cost estimation. The quality of SLRs was fair with only three scoring less than 2 out of 4. Conclusions: Currently, the topic areas covered by SLRs are limited. European researchers, particularly those at the Simula Laboratory appear to be the leading exponents of systematic literature reviews. The series of cost estimation SLRs demonstrate the potential value of EBSE for synthesising evidence and making it available to practitioners. ! 2008 Elsevier B.V. All rights reserved.
Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records
(2012)

BACKGROUND
The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification.


METHODS
We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors.


RESULTS
The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003-2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist.


CONCLUSION
We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors.
On the Resolution Limits of Superimposed Projection
(2007)

Multi-projector super-resolution is the dual of multi-camera super-resolution. The goal of projector super-resolution is to produce a high resolution frame via superimposition of multiple low resolution subframes. Prior work claims that it is impossible to improve resolution via superimposed projection except in specialized circumstances. Rigorous analysis has been previously restricted to the special case of uniform display sampling, which reduces the problem to a simple shift-invariant deblurring. To understand the true behavior of superimposed projection as an inverse of classical camera super-resolution, one must consider the effects of non-uniform displacements between component subframes. In this paper, we resolve two fundamental theoretical questions concerning resolution enhancement via superimposed projection. First, we show that it is possible to reproduce frequencies that are well beyond the Nyquist limit of any of the component subframes. Second, we show that nonuniform sampling and pixel reconstruction functions impose fundamental limits on achievable resolution.
Droop control in LV-grids
(2005)

Remote electrification with island supply systems, the increasing acceptance of the microgrids concept and the penetration of the interconnected grid with DER and RES require the application of inverters and the development of new control algorithms. One promising approach is the implementation of conventional f/U-droops into the respective inverters, thus down scaling the conventional grid control concept to the low voltage grid. Despite contradicting line parameters, the applicability of this proceeding is outlined and the boundary conditions are derived
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization
(2011)

We give novel algorithms for stochastic strongly-convex optimization in the gradient oracle model which return a O( 1 T )-approximate solution after T iterations. The first algorithm is deterministic, and achieves this rate via gradient updates and historical averaging. The second algorithm is randomized, and is based on pure gradient steps with a random step size. This rate of convergence is optimal in the gradient oracle model. This improves upon the previously known best rate of O( log(T ) T ), which was obtained by applying an online stronglyconvex optimization algorithm with regret O(log(T )) to the batch setting. We complement this result by proving that any algorithm has expected regret of Ω(log(T )) in the online stochastic strongly-convex optimization setting. This shows that any online-to-batch conversion is inherently suboptimal for stochastic strongly-convex optimization. This is the first formal evidence that online convex optimization is strictly more difficult than batch stochastic convex optimization.
Oxytocin Attenuates Amygdala Reactivity to Fear in Generalized Social Anxiety Disorder
(2010)

Patients with generalized social anxiety disorder (GSAD) exhibit heightened activation of the amygdala in response to social cues conveying threat (eg, fearful/angry faces). The neuropeptide oxytocin (OXT) decreases anxiety and stress, facilitates social encounters, and attenuates amygdala reactivity to threatening faces in healthy subjects. The goal of this study was to examine the effects of OXT on fear-related amygdala reactivity in GSAD and matched healthy control (CON) subjects. In a functional magnetic resonance imaging study utilizing a double-blind placebo-controlled within-subjects design, we measured amygdala activation to an emotional face matching task of fearful, angry, and happy faces following acute intranasal administration of OXT (24 IU or 40.32 μg) and placebo in 18 GSAD and 18 CON subjects. Both the CON and GSAD groups activated bilateral amygdala to all emotional faces during placebo, with the GSAD group exhibiting hyperactivity specifically to fearful faces in bilateral amygdala compared with the CON group. OXT had no effect on amygdala activity to emotional faces in the CON group, but attenuated the heightened amygdala reactivity to fearful faces in the GSAD group, such that the hyperactivity observed during the placebo session was no longer evident following OXT (ie, normalization). These findings suggest that OXT has a specific effect on fear-related amygdala activity, particularly when the amygdala is hyperactive, such as in GSAD, thereby providing a brain-based mechanism of the impact of OXT in modulating the exaggerated processing of social signals of threat in patients with pathological anxiety.
Generalized State Coherence Transform for multidimensional localization of multiple sources
(2009)

In our recent work an effective method for multiple source localization has been proposed under the name of cumulative State Coherence Transform (cSCT). Exploiting the physical meaning of the frequency-domain blind source separation and the sparse time-frequency dominance of the acoustic sources, multiple reliable TDOAs can be estimated with only two microphones, regardless of the permutation problem and of the microphone spacing. In this paper we present a multidimensional generalization of the cSCT which allows one to localize several sources in the P-dimensional space. An important approximation is made in order to perform a disjoint TDOA estimation over each dimension which reduces the localization problem to linear complexity. Furthermore the approach is invariant to the array geometry and to the assumed acoustic propagation model. Experimental results on simulated data show a precise 2-D localization of 7 sources by only using an array of three elements.
An Overview of BioCreative II.5
(2010)

We present the results of the BioCreative II.5 evaluation in association with the FEBS Letters experiment, where authors created Structured Digital Abstracts to capture information about protein-protein interactions. The BioCreative II.5 challenge evaluated automatic annotations from 15 text mining teams based on a gold standard created by reconciling annotations from curators, authors, and automated systems. The tasks were to rank articles for curation based on curatable protein-protein interactions; to identify the interacting proteins (using UniProt identifiers) in the positive articles (61); and to identify interacting protein pairs. There were 595 full-text articles in the evaluation test set, including those both with and without curatable protein interactions. The principal evaluation metrics were the interpolated area under the precision/recall curve (AUC iP/R), and (balanced) F-measure. For article classification, the best AUC iP/R was 0.70; for interacting proteins, the best system achieved good macroaveraged recall (0.73) and interpolated area under the precision/recall curve (0.58), after filtering incorrect species and mapping homonymous orthologs; for interacting protein pairs, the top (filtered, mapped) recall was 0.42 and AUC iP/R was 0.29. Ensemble systems improved performance for the interacting protein task.
Requirements, Traceability and DSLs in Eclipse with the Requirements Interchange Format (ReqIF)
(2011)

Requirements engineering (RE) is a crucial aspect in systems development and is the area of ongoing research and process improvement. However, unlike in modelling, there has been no established standard that activities could converge on. In recent years, the emerging Requirements Interchange Format (RIF/ReqIF) gained more and more visibility in industry, and research projects start to investigate these standards. To avoid redundant efforts in implementing the standard, the VERDE and Deploy projects cooperate to provide a stable common basis for RIF/ReqIF that could be leveraged by other research projects too. In this paper, we present an Eclipse-based extensible implementation of a RIF/ReqIF-based requirements editing platform. In addition, we are concerned with two related aspects of RE that take advantage of the common platform. First, how can the quality of requirements be improved by replacing or complementing natural language requirements with formal approaches such as domain specific languages or models. Second, how can we establish robust traceability that links requirements and model constructs and other artefacts of the development process. We present two approaches to traceability and two approaches to modelling. We believe that our research represents a significant contribution to the existing tooling landscape, as it is the first clean-room implementation of the RIF/ReqIF standard. We believe that it will help reduce gaps in often heterogeneous tool chains and inspire new conceptual work and new tools.
FRPAs and High-Gain Directional Antennas
(2012)

Many types of GNSS antennas have been developed in recent years to make them suitable for different applications. Since their designs and performance requirements vary depending on their application, they have been grouped into six different categories in this book: 1. The design and performance of each type of antenna will be described here and throughout the rest of the book. This chapter discusses the design of the first two varieties: FRPAs and high-gain directional antennas. Figure 2.1 shows a representative sample of these antennas. FRPAs are the most popular and widely used of all GNSS antennas. There are many different types of these antennas; hence they will need two chapters—this chapter and Chapter 3—to fully cover all the important types. This chapter will discuss the following FRPA designs: microstrip patch antennas, which are the most ubiquitous of all GNSS antennas, and quadrifilar helix antennas (QHAs), which are also popular for handheld receivers and crossed " drooping " bow-type dipoles, which provide relatively wider bandwidths and good circular polarization. Spiral antennas such as the Archimedean spiral antenna will be discussed in Chapter 3 under multiband antennas since they are ultrawideband and can cover the entire GNSS band from 1.1 to 1.6 GHz. The conical spiral antenna is also a high-gain di
$V_{T}$ Compensation Circuit for AM OLED Displays Composed of Two TFTs and One Capacitor
(2007)

In this paper, we propose the threshold-voltage compensation pixel circuit that is composed of two thin-film transistors (TFTs) and one capacitor (2T1C). It not only compensates the deviation of the threshold voltage of the driver TFT but also actualizes the large aperture ratio for organic light-emitting diode (OLED) devices as well as the traditional 2T1C circuit. We show the result of SPICE simulation for the pixel circuit; it indicates that the circuit can allocate the relatively large aperture ratio for OLED devices